Effects of antibiotic resistance genes on health risks of rivers in habitat of wild animals under human disturbance – based on analysis of antibiotic resistance genes and virulence factors in microbes of river sediments

Abstract Studying the ecological risk of antibiotic resistance genes (ARGs) to wild animals from human disturbance (HD) is an important aspect of “One Health”. The highest risk level of ARGs is reflected in pathogenic antibiotic‐resistant bacteria (PARBs). Metagenomics was used to analyze the characteristics of PARBs in river sediments. Then, the total contribution of ARGs and virulence factors (VFs) were assessed to determine the health risk of PARBs to the rivers. Results showed that HD increased the diversity and total relative abundance of ARG groups, as well as increased the kinds of PARBs, their total relative abundance, and their gene numbers of ARGs and VFs. The total health risks of PARBs in wild habitat group (CK group), agriculture group (WA group), grazing group (WG group), and domestic sewage group (WS group) were 0.067 × 10−3, −1.55 × 10−3, 87.93 × 10−3, and 153.53 × 10−3, respectively. Grazing and domestic sewage increased the health risk of PARBs. However, agriculture did not increase the total health risk of the rivers, but agriculture also introduced new pathogenic mechanisms and increased the range of drug resistance. More serious was the increased transfer risk of ARGs in the PARBs from the rivers to wild animals under agriculture and grazing. If the ARGs in the PARBs are transferred from the rivers under HD to wild animals, then wild animals may face severe challenges of acquiring new pathogenic mechanisms and developing resistance to antibiotics. Further analysis showed that the total phosphorus (TP) and dissolved organic nitrogen (DON) were related to the risk of ARGs. Therefore, controlling human emissions of TP and DON could reduce the health risk of rivers.


| INTRODUC TI ON
"One Health" suggests that model of human-animal-environmental health is closely related, but in fact, the model is almost controlled by humans (Zinsstag et al., 2023).The harmonious balance of the model could be disrupted by negative human disturbance (HD), resulting in the degradation of natural environment (Acheampong & Opoku, 2023;Jokanović et al., 2021;Zhang et al., 2020) and the deterioration of animal health (Doherty et al., 2021;Miller et al., 2023).
Nature reserves of wild animals play a pivotal role in protecting rare and endangered wild animals and ensuring ecological security (Wang, Liu, et al., 2021).In China, to harmonize the protection of wild animals and the development of human society, numerous policies have been introduced in recent decades, but the contradictions between the two are often difficult to reconcile (Guo & Wu, 2023), and the ecological networks in nature reserves face escalating challenges as a result of increasing HD (Gu et al., 2023).The presence of significant HD in the nature reserves of wild animals, as mentioned, establishes a certain antagonistic relationship with the habitat of wild animals (Qiu, 2015).Thus, studying the ecological risks of HD in nature reserves of wild animals becomes crucial for understanding and mitigating the challenges of the contradictions between the protection of wild animals and the development of human society.
Microbial risk is indeed a significant aspect of "One Health" (Wu et al., 2023), and it is also an important component for assessing environmental health risks (Abdugheni et al., 2023).Antibiotic resistance genes (ARGs) in microbes represent a critical concern when evaluating microbial risks (Li et al., 2022;Shao et al., 2018).HD plays a crucial role in fostering the proliferation of ARGs (Czekalski et al., 2015;Pruden et al., 2012).Aquatic ecosystems, frequently impacted by humans, serve as reservoirs for ARGs and provide an optimal environment for the accumulation and dissemination of ARGs (Marti et al., 2014;Rout et al., 2024;Rout, Das, et al., 2023).And rivers are one of the main containers for livestock and poultry farms runoff, fertilizer runoff and rural domestic sewage, which are widely recognized as significant contributors to the accumulation of ARGs in rivers (Chen et al., 2015;Cheng et al., 2013;Mware et al., 2022).
In China, rivers crisscross the nature reserves of wild animals, which are suffering from HD such as farming, animal husbandry, and domestic sewage emissions that are sources of ARGs (Lu et al., 2022;Zhang et al., 2014).For the ARGs in rivers could enter the body by drinking water (Zhang, Qin, et al., 2021), it is indicated that the ARGs in the rivers with nature reserves of wild animals could be moved to wild animals by drinking.The gut microbiota plays a vital role in the health of wild animals by providing essential nutritional services and protection against the invasion of intestinal pathogens (Fackelmann et al., 2021), and regulating multiple aspects of microbial metabolite pools that could affect the gut barrier and the polarization of immune cells (Tan et al., 2023).Many studies have shown that ARGs can be transferred into the gut microbiota (Khan et al., 2020;Lamberte & van Schaik, 2022;Rolain, 2013), if the ARGs entry into the gut will have a significant impact on the gut microbiota, which may lead to various diseases and represent unknown risks to wild animals (Zhu et al., 2021).
However, not all ARGs pose risks to ecosystems.Most studies have found that ARGs are present even in places where humans have never been (Kim et al., 2022;Luo et al., 2021;Zeng et al., 2019).
Therefore, when assessing the risk of ARGs to ecosystems, the risk level of ARGs should be categorized, with pathogens containing both ARGs and virulence factors (VFs) representing the highest risk level of ARGs (Martínez et al., 2015).On the one hand, drug-resistant pathogens cause disease and render antibiotic treatment ineffective (Pan et al., 2020); on the other hand, co-adaptation of virulence and resistance often gives the pathogens a greater advantage, which may pose unknown ecological risks.In metagenomic assembly genomes (MAGs) of microbes, if a MAG contains one or more ARGs and VFs, the MAG could be potential pathogenic antibiotic-resistant bacterium (PARB) (Liang et al., 2020).Some studies have used PARBs to assess microbial risks to ecosystems under HD.For example, Liang et al. (2020) studied the occurrence of PARBs in aquatic environments impacted by HD and found that HD leads to high microbial risk, which was reflected in the high proportion of MAGs identified as PARBs, as well as the high abundance and density of PARBs in human-disturbed areas, also confirmed that 81.8% of PARBs are related to known pathogenic taxa.Zou, Xiao, et al. (2023) investigated the effect of wastewater treatment plants effluent discharge on the microbiological risks of low-flow rivers and also found the high proportion of PARBs in effluent-dominated rivers.Both of these studies indicated that intragenomic ARGs-VFs coexistence seemed more likely to occur in regions affected by HD, also indicated the higher microbial risks in rivers under HD.Therefore, the occurrence of PARBs in river ecosystems should be of great concern.However, there is still a lack of research on the use of PARBs to analyze the health risks of ARGs to rivers in nature reserves of wild animals, where there is often a close interaction between humans and wild animals.
Studying the factors that influence the risk of ARGs in rivers under HD plays an important role in reducing the ecological risk of HD to rivers (Na et al., 2018;Rout, Tripathy, et al., 2023).HD will not only directly increase the risk of ARGs (Zhang et al., 2022), but also increase the risk of ARGs by altering environmental factors, which have been proposed for shaping ARG profiles (Zhao et al., 2023).
In addition, the environmental factors of rivers have the potential to induce shifts in the structure of river microflora (Wang, Fan, et al., 2021), which is also closely related to the risk of ARGs (Zhou et al., 2017).Furthermore, the spread of ARGs in pathogens from rivers in habitats of wild animals is a matter of great concern (Zhang, Gaston, et al., 2021).ARGs could be horizontally transferred by mobile genetic elements (MGEs) in the environment (Jeon et al., 2023), thus the MGEs in PARBs may play an important role in the transfer of ARGs from rivers to the gut microbiome of wild animals.Now in China, the case of HD for survival is unavoidable, and it is crucial to study the causes of the factors affecting the risk of ARGs from the rivers to wild animals in the habitats under HD.
Our study aims to explore the effects of HD of agriculture, grazing, and domestic sewage in China's nature reserves of wild animals on the health risks of ARGs in rivers, as well as to find the main | 3 of 14 factors affecting the health risks of ARGs from rivers to wild animals.The characteristics of ARGs in microbes of river sediments were examined to study the impact of HD on the ARGs, the total contribution of ARGs and VFs in PARBs were assessed by factor analysis to measure the risk to river health, and the plasmids that carried ARGs in PARBs were identified to determine the transfer risk of ARGs in PARBs.Lastly, the influence of environmental factors of the river sediments on health risks of ARGs to the rivers were explored.Our study could be offered informed perspectives for sustainable human activities in the nature reserves of wild animals, aiming at a "win-win" scenario that balances the economic and life development of the inhabitants of these reserves with the imperative of wildlife conservation.

| Sample collection
Baihe National Nature Reserve (104°01′-104°12′ E, 33°10′-33°22′ N) is a habitat for endangered wild animals such as giant pandas (Ailuropoda melanoleuca) and snub-nosed golden monkeys (Rhinopithecus roxellana) in China.Our previous study found that HD increased the health risk of gut microbes in golden monkeys because primates are more likely to acquire ARGs and VFs from sources of HD (Zou, Yuan, et al., 2023).The investigation showed that HD such as grazing, farmland cultivation, and domestic sewage discharge were typical and severe in the Baihe National Nature Reserve.Therefore, we chose to conduct our study in the Baihe National Nature Reserve.
In the Baihe National Nature Reserve, the river flows from southwest to northeast.We sampled river sediments from the areas disturbed by human activities, including agriculture, grazing, and domestic sewage; the sediments of the rivers under agriculture, grazing, and domestic sewage were defined as WA group, WG group, and WS group, respectively.At the same time, we sampled sediments from the upstream of the rivers that had never been disturbed by humans (wild habitat) and defined these sediment samples as check control (CK group).Although some sections of the downstream of the rivers are undisturbed by humans, we could not be sure whether pollutants from HD had migrated downstream (north) with the flow of the water in the rivers and affected the sediments in the wild hab- set up three replicates of each type of HD.Twelve sediment samples in total were then carefully preserved in dry ice and transported to the laboratory (Figure 1).

| DNA extraction
DNA extraction from the sediments was conducted using the FastDNA® Spin Kit for Soil (MP Biomedicals, France).The quantification and purity of the extracted DNA were subsequently assessed using a NanoDrop™ spectrophotometer.DNA samples meeting the criteria of an absorbance ratio between 260 and 280 nm falling in the range of 1.8-2.0 were considered suitable for metagenomic sequencing.The process of DNA extraction was conducted by the laboratory at Shanghai Magi Biological Company, China (Meiji Biological Medicine Co., Ltd., Shanghai, China).Each sample was extracted three times as described above, and eligible DNA from all three times was pooled for subsequent analysis.

| Metagenomic sequencing
We used Covaris M220 (Gene Company Limited, Shanghai, China) to fragment the obtained DNA and subsequently screened fragments of approximately 400 bp to construct the paired-end library using NEXTFLEX Rapid DNA-Seq according to the manufacturer's instructions.HiSeq 2000 (Illumina Inc., San Diego, CA, USA) was selected for metagenomic sequencing of the paired-end library at Majorbio Bio-Pharm Technology Co., Ltd.(Shanghai, China).The data were deposited into the NCBI Sequence Read Archive (SRA) database under accession number PRJNA1044275.For the obtained metagenomic data, we used fastp to perform quality clipping of adapter sequences from reads and remove low-quality reads (reads <50 bp in length with an average mass value of <20 and containing N bases) (Zhang et al., 2017).The reads were compared with the host genome sequence using BWA software (https:// biobwa.sourc eforge.net).Reads with high similarity were removed to obtain clean reads for subsequent analysis.Next, clean reads were assembled using Megahit for contigs, and contigs with the shortest sequence longer than 300 bp were retained (Li et al., 2015).We used MetaGene to perform an open reading frame prediction of the retained contigs (length of reads ≥100 bp), and the per-base coverage depth across all contigs was calculated by mapping raw reads from each sample (Zhu et al., 2010).CD-HIT was used to construct the coverage >90% and identity >90% of predicted gene sequences of all samples as a nonredundant gene contig.The identity ≥0.95 of nonredundant gene contig was blasted using SOAPaligner, and gene abundance of the nonredundant gene contigs was subsequently calculated.Then, the nonredundant gene contig was predicted as the open reading frame (ORF), and the ORFs were used in card_v3.0.9 (the Comprehensive Antibiotic Research Database) to obtain ARGs (http:// arpca rd.mcmas ter.ca, (accessed on 28 November 2022); blastp, e-value: 1 × 10 −5 ).And plasmids in ACLAM were used to obtain MGEs (blastp, e-value: 1 × 10 −5 ).An identity >80% of ARGs and MGEs were selected for analysis.
To compare coverage between different samples, the coverage of ARG-like ORFs and MGE-like ORFs was normalized using the data size of each sample (copies/Gb) (Ma et al., 2016).
The coverage of each MAG was calculated as the average scaffold coverage, and each scaffold was weighed by its length in base pairs.Then, the relative abundance of each MAG was calculated as its coverage divided by the total coverage of all genome bins.Thus, the relative abundance of each MAG was calculated as the number of reads (based on average coverage) aligning to the MAG normalized by the total number of reads in the sample.The calculation formula was as follows: where A i , C i , and N i represent the relative abundances, coverage, and contig numbers of i MAG, respectively.N is the total number of reads in the samples.

| Identification of plasmids
To further evaluate the risk of transmission, it is imperative to ascertain the location of ARGs in each PARB.To accomplish this, we used the plasmid prediction tool RFPlasmid to identify the plasmids in MAGs (van der Graaf-van Bloois et al., 2021).The MAG was uploaded to the webpage (klif.uu.nl/ rfpla smid/ ), where the Generic model was selected, and the submission was made.Then, we selected the scaffolds that identified as plasmids (votes plasmid >0.5), and the ARGs identified in scaffolds of MAGs were compared with the plasmid scaffolds to analyze the ARGs carried by the plasmid in PARBs. (1)

| River health risk assessment
Four independent variables were considered, including the types and numbers of ARGs and VFs in each PARB in the CK group, the WA group, the WG group and the WS group.To quantify these variables, we tabulated the classes and gene counts of ARGs and VFs in each PARB for the four groups.Subsequently, we conducted factor analysis to extract the principal component features based on these variables.The total scores of the principal component features were computed using Formula (2).The higher scores indicated the greater contribution of ARGs and VFs to the risk of each PARB.Since the health risk of a PARB is influenced by its abundance, we determined the health risk for each PARB using Formula (3).Finally, the total health risk for all PARBs in each group was calculated using Formula (4).The conceptual framework of the health risk assessment for rivers and wild animals is shown in Figure 2.
where i is the number of component features considered in each of the four groups, S i is the score of the component features, W i is the weight of S i and F i is the total score of the PARB.HR i is the health risk of one individual PARB, and THR is the total health risk of PARBs in (2) each group.The higher THR value indicates a greater health risk to the river ecosystem.

| Environmental factor measurements
We used the pH meter (PHS-3C, China) to measure the pH of the sediments.Available phosphorus (AP) was determined using the sodium bicarbonate extraction-molybdenum-antimony anti-spectrophotometric method (Olsen, 1954).Available potassium (AK) extracted using the 1 M CH 3 COONH 4 solution and then analyzed using the flame atomic absorption spectrophotometer (Varian AA240, USA).Slowly available potassium (SAK) extracted using the COD Digestion instrument (Hach DRB200, China), and flame photometer (Perkin Pin AAcle 900F, USA) was used for measurement.Dissolved organic carbon (DOC) was extracted using MK 2 SO 4 solution and quantified using a TOC-TN analyzer (Shimadzu, Japan) (Shi et al., 2018).The content of dissolved organic nitrogen (DON) was determined by calculating the difference between total nitrogen (TN) and inorganic nitrogen, and TN was determined using the Kjeldahl method.Total phosphorus (TP) was determined using the sodium hydroxide melting-molybdenum antimony anti-colorimetric method.Total potassium (TK) was determined using the sodium hydroxide melting-flame atomic absorption spectrophotometry method.

| Statistical analysis and visualization
In our analysis, one-way analysis of variance (ANOVA) and t-tests were used to examine the differences between samples for ARGs with a significance level of p < .05using SPSS Statistics 27 (IBM, Armonk, USA).The contig numbers of ARGs and VFs at the type level and microbes were used to calculate their Simpson's index using the R package "vegan" (Oksanen et al., 2017).Principal component analysis (PCA, Canoco 5.0, Microcomputer Power, New York, NY, USA) was used to investigate the relationship between environmental factors and microbial characteristics.Histograms and heatmaps, and Pearson's correlation analysis were performed using OriginPro 2021.Map was created using ArcGIS 10.2 (ESRI Corp. 2013).

| The effect of HD on the ARGs of river sediment microbes in the reserve of wild animals
The Simpson's index of ARGs in river sediments of the WA group, WG group, and WS group were significantly higher than that of the CK group (Figure 3a; ANOVA, p < .05).The total relative abundance of ARGs in the WA group and WG group were significantly higher than that in the CK group (Figure 3b; t-test, p < .05).A total of 16 classes of ARGs were identified in river sediment samples from four groups, of which Nucleoside, Peptide, Mupirocin, Phenicol, Beta-lactam, and Sulfonamide were exclusively found in sediments impacted by HD but not detected in the CK group (Figure 3b).

| The effect of HD on PARBs of river sediment microbes in the reserve of wild animals
In total, there were 157 kinds of MAGs in the river sediments of nature reserve of wild animals.While only 49 kinds of MAGs were identified as potential PARBs (Table S1).Among these MAGs, there  S1).

| The effect of HD on the health risk of the river in the reserve of wild animals
As shown in shown in Table S2.

| The effect of HD on the transfer risk of ARGs in PARBs of river sediment microbes in the reserve of wild animals
There were no ARGs carried by plasmids in the PARBs of the CK group and WS group, while there were three kinds and two kinds of PARBs containing three classes (three genes) and seven classes (eight genes) of ARGs carried by plasmids in the WA group and WG group (Table 2).

| The effect of environmental factors on the microbial risks in the rivers
PCA can be used to combine the results of environmental factors and microbial risks to provide a deeper understanding of the underlying drivers of the health risks.A total of 45.46% of the variance was explained by PCA1, 34.26% by PCA2, and 79.72% by the two-axes cumulative variance.The content of TN and TK had direct effect on PARBs, while other content of nutritious substances was mainly affected the diversity of ARGs and the relative abundance of MGEs, which exhibited positive correlations.(Figure 5a).
Further analysis using simple correlation showed that the DARGs had a significant positive correlation between the content of TP and DON (p < .05).pH was positively correlated with AMGEs (p < .05) (Figure 5b).The content of the most nutritious substances in HD groups were higher than those in the CK group (Table S4).

| DISCUSS ION
The higher the Simpson's index of ARGs in the environment indicates the higher the risk of ARGs to the ecological system (Yang et al., 2019).Our results showed that the Simpson's index of ARGs of ARGs in pathogens (Liu et al., 2021), this also indicated that HD could increase the risk of ARGs in the rivers of reserves of wild animals, and the risk of drug-resistant pathogens to wild animals were needed further analysis.
The PARBs reflected the highest risk level of ARGs (Martínez et al., 2015).Unfortunately, PARBs were found in the rivers in the nature reserve of wild animals.The species of PARBs, as well as the total numbers of ARGs and VFs in the PARBs, were increased by HD, and some researches supported our findings (Liang et al., 2020;Zou, Xiao, et al., 2023), also indicating that HD increased the risks of Note: "TFS" is the total factor score; "HR" is the health risk of each PARB; "THR" is the total health risks of PARBs.
| 9 of 14 HU et al.However, the total contribution of ARGs and VFs in PARBs should be considered when the risk of PARBs in the ecological environment is evaluated.Several studies using factor analysis had shown that the higher contribution of ARGs and VFs in a PARB lead to the higher the health risk of the PARB (Bai et al., 2020;Zou, Yuan, et al., 2023).Our results indicated that grazing and domestic sewage could enhance the contribution of ARGs and VFs to the risk of PARBs in rivers, and grazing had the greatest contribution to the risk of PARBs.Moreover, the risk of a PARB to the environment was also affected by its abundance (Liu et al., 2021).It was found that the total relative abundance of PARBs in the river sediments under grazing and domestic sewage was higher than that without HD, resulting in the higher total health risks of PARBs under grazing and domestic sewage.The results also showed that the contribution of the factors belonged to ARGs was higher than that belonged to VFs, indicating that ARGs contributed more to the health risk of PARBs than VFs.

Groups
Overall, grazing and domestic sewage could increase the risk of ARGs in PARBs to the rivers, which was mainly reflected in two aspects.On the one hand, the pathogenic mechanisms and the drug resistance scope of the PARBs were increased by grazing and domestic sewage.On the other hand, the risks of multidrug PARBs were increased by grazing and domestic sewage.Multidrug PARBs carrying multidrug resistance genes pose a severe threat to public health risks and increase the risk of superbugs (Zhao et al., 2020), and the kinds of multidrug PARBs in the WG group and WS group were more than that in the CK group.These two aspects indicated that the risk of pathogenic infections in wild animals increased, and the scope of antibiotic resistance will be greatly expanded if wild animals are treated with antibiotics.
In summary, grazing and domestic sewage increased the serious potential risks of PARBs to rivers in the reserve of wild animals.
If these PARBs enter wild animal populations through rivers, they may cause extreme health hazards to wild animals and may not be treated well with antibiotics.But, we surprisingly found that although agriculture could increase the total abundance of ARGs, it was determined to reduce the risk of PARBs.The risk of PARBs in the WA group could be diluted by other bacteria, the low contribution of ARGs and VFs to the risk of PARBs seems to confirm that.
However, it also indicated a potential problem that non-pathogenic and opportunistic bacteria might carry a large number of ARGs.
Although these bacteria did not significantly increase the risk of PARBs, most studies have shown that the microbial risks posed by these bacteria cannot be ignored (Alexander et al., 2015;Bouki et al., 2013;Serwecińska, 2020).
MGEs play a pivotal role in the horizontal transfer of genes (Kumkar et al., 2022).Plasmids are particularly important MGEs, serve as crucial carriers for the transmission of ARGs (Zhu et al., 2023).The horizontal transfer of ARGs through plasmids increases the risk of superbug in the environment (Pan et al., 2020).
Our study indicated that the PARBs under all kinds of HD had the risk from the rivers to wild animals in the nature reserve of wild animals, and agriculture and grazing increased the transfer risks of ARGs in PARBs to wild animals because agriculture and grazing increased the total numbers of ARGs carried by plasmids in PARBs.
Our results indicated that the transfer risks of ARGs in PARBs under grazing was the highest, for the gene numbers of ARGs were the highest, as well as the resistance scopes were the widest.In addition, it is noteworthy that most of the transferable ARGs in the WG group came from G_bin41, so we believe that the monitoring of this PARB should be strengthened.Fortunately, our results also indi- Environmental factors are key drivers of microbial risks (Chen et al., 2021).Based on PCA analysis, we found that the environmental factors also had impacts on the risk of PARBs.Specifically, the content of TN and TK would mainly affect the risks of PARBs by affecting the relative abundance of PARBs, while the content of DON, TP, AP, DOC, SAK, and AK, and pH affecting the diversity and transfer ability of ARGs, our results were supported by some previous researches (Liu et al., 2021;Zhang et al., 2018).Unfortunately, we found that the agriculture, grazing and domestic sewage could increase the content of nutritious substances.Once the contaminants from HD enter the water, they probably have various effects on the risk of ARGs (Boto et al., 2019), which supported our results that HD could increase the risk of ARGs by increasing the content of nutritious substances.
Further analysis found that pH was positively correlated with the abundance of MGEs, and Xu et al. (Xu et al., 2022) showed that the high pH might promote the spread of ARGs in the environment, which indicated that the higher the pH, the higher the possibility of MGEs to transfer ARGs.Both of the pH under agriculture and grazing was higher than wild habitat, while the pH under domestic sewage was lower than wild habitat, for domestic sewage may contain some substances such as cellulose, starch, sugars, fatty, and proteins, which could produce acidic substances such as hydrogen sulfide and volatile fatty acids, phosphoric acid, and carbonic acid in the anaer-  et al., 2010).The lower pH could also be used to explain why MGEs were not checked under domestic sewage.
In addition, the content of TP and DON were positively correlated with the diversity of ARGs, which indicated that the higher content of TP or DON could promote an increase in the higher risk of ARGs.However, VFs did not significantly correlate with other environmental factors, which indicated that the contamination from HD increased health risk of rivers by increasing the risk of ARGs rather than the risk of VFs.There was also a significant correlation between the content of TP and DON, which indicated that these two nutrients would have a synergistic effect to enhance the risk of ARGs.These results could be explained in water environments, and it is noteworthy that water environments are forced to receive amounts of nutritious substances from HD (Boxall et al., 2012).Our study released a significant health concern to protect wild animals.
Nitrogen and phosphorus are the main indicators of water eutrophication (Conley et al., 2009).Agriculture, grazing, and domestic sewage are the main sources of nitrogen and phosphorus to rivers (Eliassen & Tchobanoglous, 1969;Nelson et al., 1996;Sharpley et al., 1987), and our result showed that HD increased the content of nitrogen and phosphorus.Thus, we suggest that grazing manure could be collected or buried with soil.Composting has been shown by most studies to reduce the microbial risks (Gou et al., 2018;Singh & Nain, 2014), the domestic waste and feces could be composted for agriculture, which would reduce the need for chemical fertilizers and reduce the input of nitrogen and phosphorus from agriculture and domestic sewage into rivers.To achieve these practices, it is necessary to focus on the planning of production activities, rigorously managing wastewater discharge methods, and promptly implementing measures to improve wastewater treatment protocols.
Most importantly, we emphasized while protecting wild animals, we must strengthen to monitor the health risk of rivers in nature reserves of wild animals, especially the risk of ARGs.

| CON CLUS ION
It was determined that HD increased the diversity of ARGs in river sediments in the nature reserve of wild animals.We found that grazing and domestic sewage increased the health risk of rivers, and the risk of ARGs in PARBs being transferred to wild animals under grazing was higher than that of wild habitat.The total health risks of agriculture were lower than that of wild habitat, but agriculture introduced new pathogenic mechanisms and increased the range of resistance to PARBs, and enhanced the potential risk of transfer of ARGs in PARBs.Therefore, agriculture, grazing, and domestic sewage increased the health risk of PARBs in rivers of the nature reserve of wild animals, and agriculture and grazing increased the risk of ARGs in PARBs being transferred to wild animals.Among them, domestic sewage posed the greatest health risk to rivers, but grazing posed the greatest risk of ARGs being transferred from PARBs in the rivers to wild animals.The contribution of ARGs to river health was greater than that of VFs.HD mainly increased the risk of ARGs to increase the health risk of rivers by discharging nitrogen and phosphorus into rivers.Therefore, we suggest that under the premise that HD for survival cannot be avoided, we should control the anthropogenic discharge of nitrogen and phosphorus into rivers, and detect the content of nitrogen and phosphorus, so as to control the risk of ARGs from HD to river health.

CO N FLI C T O F I NTER E S T S TATEM ENT
None declared.
itat.In addition, there are roads built along the northern part of the rivers where wild animals do not occur.Sampling was conducted in June 2022, with samples collected from three different locations near the center of rivers at each site.The column sampler was used to collect the top 10 centimeters of sediments.To minimize the impact of geographic patterns, the distance among our sampling sites cannot be too far.In order to minimize the errors due to sampling, we F I G U R E 1 (a) Baihe National Nature Reserve and sampling points.(b) Overview of sampling surroundings.Image created with BioRe nder.com, with permission.

E 2
Conceptual framework of the health risk assessment.F I G U R E 3 The effect of HD on ARGs of river sediment microbes in the reserve of wild animals.(a) The Simpson's index of ARGs.Different letters indicate significant differences in the Simpson's index between the various groups (p < .05).(b) The relative abundance and composition of ARGs.The "*" indicates a significant difference in total relative abundance between the two groups (p < .05).The symbol "(−)" denotes the absence of specific classes of ARGs in the CK group.
in rivers was increased by agriculture, grazing, and domestic sewage, which indicated that HD increased the risk of ARGs to the rivers in the habitat of wild animals.For the Simpson's index provides a comprehensive assessment by considering both the type and abundance of ARGs, and the agriculture and grazing imported new classes of ARGs to the rivers and significantly increased the total abundance of ARGs, while the domestic sewage only imported new classes of ARGs to the rivers.In other words, the significant increase in the abundance and the introduction of new types of ARGs were the reason for the increased the risk of ARGs by agriculture and grazing, while the introduction of new types of ARGs was the reason for the increased risk of ARGs by domestic sewage.Further analysis indicated that if the ARGs from the rivers under agriculture and grazing to the wild animals, then the wild animals had the potential risk of developing resistance of Sulfonamide, Beta-lactam, Phenicol, Mupirocin, Peptide, and Nucleoside, while ARGs in the rivers under domestic sewage had the risk that made wild animals develop resistance of Sulfonamide, Beta-lactam, Phenicol, and Mupirocin.The intrusion of HD into diverse environments contributes to heightened selective pressure on microbes, which favors the proliferation

F
I G U R E 5 (a) The effect of various environmental factors on key microbial characteristics.The microbial characteristics included DARGs (diversity of ARGs), DVFs (diversity of VFs), AMGEs (relative abundance of MGEs), and APARBs (relative abundance of PARBs).(b) The correlation between environmental factors and microbial characteristics, where "*" indicates statistically significant correlations at p ≤ .05. rivers by increasing the kinds of PARBs, as well as their resistance and pathogenicity.Further analysis revealed that HD could increase the new types of ARGs and VFs in the PARBs.Agriculture could increase the classes of ARGs such as Fosfomycin, Fluoroquinolone antibiotic, Macrolide antibiotic, and Mupirocin, and VFs such as Biofilm, Exoenzyme, Motility, and Stress survival; grazing could increase the classes of ARGs such as Diaminopyrimidine antibiotic, Fosfomycin, Lincosamide antibiotic, Macrolide antibiotic, Phenicol antibiotic and Penam, and VFs such as Biofilm, Exoenzyme, Exotoxin, Motility and Stress survival; domestic sewage could increase the classes of VFs such as Biofilm, Exoenzyme, Exotoxin, Motility, and Stress survival.
cated an optimistic result that not all classes of ARGs had the risk of horizontal transfer to wild animals.Because we found that among the 16 classes of ARGs detected in the habitats of wild animals, only seven classes of ARGs are at the risk of horizontal transfer to wild animals, and the ARGs classes of Aminocoumarin, Fosfomycin, Glycopeptide, Rifamycin, Fosfomycin, Fluoroquinolone, Mupirocin, Nitroimidazole, and Penam had no transfer risks from the rivers to wild animals.Overall, HD enhanced the transfer risk of ARGs through plasmids.Therefore, it was urgent to study what were the driving factors that enhanced the transfer risk of ARGs from human-disturbed habitats to wild animals.

Table 1
Health risk of each PARB and all PARBs in each group.
TA B L E 1